Presentation at the Resilience in Rome Meeting, July 2-3, 2014

1. francesco.petrini@uniroma1.it , francesco.petrini@stronger2012.com
--
*Research Associate,
School of Civil and Industrial Engineering, Sapienza Università di Roma
Via Eudossiana 18 - 00184 Rome (ITALY)
tel. +39-06-44585072
StroNGER S.r.l., Co-founder and Director
Via Giacomo Peroni 442-444, Tecnopolo Tiburtino, 00131 Rome (ITALY)
--
Informal Meeting on RESILIENCE
Rome, 2-3 July 2014
School of Civil and Industrial Engineering
University of Rome La Sapienza
StroNGERStroNGER
Structures of the Next Generation – Energy harvesting and Resilience
C. Crosti, S. Arangio, F. Petrini *, K. Gkoumas, F. Bontempi
www.stronger2012.com

2. What is StroNGER
Francesco Petrini.
francesco.petrini@ustronger2012.com

3. A spin-off research Company
Founded in November 2012
Operating in the civil and environmental engineering industry

4. Str
o N
GER
www.stronger2012.com
FromNovember2012
The research group of structural analysis and design at Sapienza Univ.

5. StroNGER – who we are
Franco Bontempi, PhD
StroNGER srl, Scientific Advisor
Prof. of Structural Analysis and Design
Sapienza University of Rome
Expertise:
-Fire Safety Engineering
-Forensic Engineering
Expertise:
-Structural Safety
-Structural Identification
Expertise:
-Wind Engineering
-Performance Based Design
Chiara Crosti, PhD
StroNGER srl, CEO
Francesco Petrini, PhD
StroNGER srl, Vice Director
Stefania Arangio, PhD
StroNGER srl, Director
Konstantinos Gkoumas, PhD
StroNGER srl, Partner
Expertise:
-Energy Harvesting
-Dependability
Francesco Petrini. Co-founder and
Director 5

6. Str
o N
GER
www.stronger2012.com
Academic research Industry research R&D
University courses Professional courses
Big group Small group
Design consultant activityResearch experience in
structural analysis
CONVERSION: StroNG points

7. StroNGER S.r.l.
a Spin-off Company (Small Medium Enterprise)
that operates in the Civil Engineering industry.
High-profile tools and methodologies that lead to structures that fulfill required
performances under a resilience and sustainability point of view.
StroNGER expertise:
•Design and rehabilitation of Civil structures and infrastructures with regard to wind,
earthquakes, waves, landslides, fire and explosions.
•Disaster resilience assessment.
•Advanced numerical modeling of Civil structures and infrastructures.
•Forensic engineering.
•Sustainability and Energy Harvesting in Civil structures and infrastructures.
StroNGER has been recently awarded by the European Space Agency
with the space technology transfer permanent award
StroNGER S.r.l. was founded in 2012 by researchers from the academic world working in the
civil engineering field, each one having more than 10 years of experience in the field
www.stronger2012.com info@stronger2012.com
Phone: +39 0644585070
Structures of the Next Generation – Energy harvesting and Resilience
ResilienceWorkshop.RomeJuly02-032014

8. Energy Harvesting
Francesco Petrini.
francesco.petrini@ustronger2012.com
StroNGER for
Structures of the Next Generation – Energy harvesting and Resilience

9. Energy Harvesting (EH) can be defined as the sum of all those processes that
allow to capture the freely available energy in the environment and convert it
in (electric) energy that can be used or stored.
Harvesting Conversion
Use
Storage
Energy harvesting - Overview
Francesco Petrini. Co-founder and
Director
Resources
Sun
Water
Wind
Temperature differential
Mechanical vibrations
Acoustic waves
Magnetic fields
…
Extraction systems
Magnetic Induction
Electrostatic
Piezoelectric
Photovoltaic
Thermal Energy
Radiofrequency
Radiant Energy
9
ResilienceWorkshop.RomeJuly02-032014

10. Applications for the energy sustainability
EH in buildings – a premise
10
• EH devices are used for powering remote monitoring sensors (e.g. temperature sensors, air
quality sensors), also those placed inside heating, ventilation, and air conditioning (HVAC) ducts.
• These sensors are very important for the minimization of energy consumption in large
buildings
Image courtesy of
enocean-alliance®
http://www.enocean-alliance.org
Francesco Petrini. Co-founder and
Director 10
ResilienceWorkshop.RomeJuly02-032014

11. Francesco Petrini. Co-founder and
Director 11
a. Steel plate (support)
b. Sensor transmitter module
c. Piezoelectric bender
d. Fin
e. Temperature probe
f. Tip mass
Proposal of space technology transfer for the design, testing, production and
commercialization of a self-powered piezoelectric temperature and humidity sensor
(PiezoTSensor), for the optimum energy management in building HVAC (Heating,
Ventilation and Air Condition) systems.
PiezoTSensor ©
HVAC upper wall
HVAC lower wall
HVAC lower wall
ResilienceWorkshop.RomeJuly02-032014

12. Francesco Petrini. Co-founder and
Director 12
PiezoTSensor ©
ResilienceWorkshop.RomeJuly02-032014
Air flow

13. Applications for the energy sustainability
Energy Harvesting for monitoring HVACs operating conditions
Currently:
•Power is provided by batteries or EH devices based on thermal or RF methods
•Sensors work intermittently (to consume less power ~ 100µW)
An EH sensor based on piezoelectric material has several advantages being capable to provide up
to 10-15 times more power than currently used devices leading to additional applications or
longer operation time.
Image courtesy of
enocean-alliance®
http://www.enocean-alliance.org
Francesco Petrini. Co-founder and
Director 13
ResilienceWorkshop.RomeJuly02-032014

14. Francesco Petrini. Co-founder and
Director 14
ResilienceWorkshop.RomeJuly02-032014
Vibration EH devices
Flow-induced EH devices
Applications for infrastructures

15. Resilience
Francesco Petrini.
francesco.petrini@ustronger2012.com
StroNGER for
Structures of the Next Generation – Energy harvesting and Resilience

16. Francesco Petrini. Co-founder and
Director 16
RISE – Concept resume
MCEER (Multidisciplinary Center for Earthquake Engineering
Research), (2006). “MCEER’s Resilience Framework”.
-- = ordinary node
= critical node in case of emergency---
= principal link (e.g. road)
HOSPITAL
HOUSE
AGGRGATE
MALL
SHOPPING
CENTEROFFICE
HOUSE
AGGRGATE
FIRE
DEPARTMENT
NUCLEAR
PLANT
HOSPITAL
HOUSE
AGGRGATE
MALL
SHOPPING
CENTEROFFICE
HOUSE
AGGRGATE
FIRE
DEPARTMENT
NUCLEAR
PLANT
= earthquake action
= blast action= fire action
Representation of a large infrastructure as a network of nodes and links
Nodes: relevant premises of the infrastructure Links: local and access roads, pipelines and supply system
Initial losses
Recovery time:
• Resourcefulness
• Rapidity
Disasterstrikes
A
L0
(dQ/dt)0
LOCAL- LEVEL:
Contributeof the single
premise(e.g. hospital,
by considering the
interrelations with
proximity elements)
NETWORK- LEVEL:
- Convolution of the local-level contributes
dLi
Quantitative definition of Resilience (MCEER) R.I.S.E. Multiscale philosophy
Disaster strikes --> Hazard scenario

17. Francesco Petrini. Co-founder and
Director 17
ResilienceWorkshop.RomeJuly02-032014
RISE–Framework
Load
Network Model for
resilience
Multi-hazard
Scenarios
Local
Level
Network
Level
Local resilience indicators Network resilience indicators
ASSESSMENTandMITIGATION
(Analysisforeachnodeandlink)
Scenario output before mitigation
Scenario output after mitigation
ResISt
framework for resilience assessment
Structure performanceA
B Recovery
E.g. Repair time
Damage
Action
Damage/Disservice
% of rescued
Action values
IM
A
IM
100 %
People safetyB
Quality
Indicator
Status of nodes and links
(no interaction)
A
Quality
Indicator
Interactions effects (quality drop)B
L0
i TR
i
Quality (network level)
Combination of local indicators
Indicator
L0 TR
Resilience ∞ 1 /A
C
Local resilience indicators are evaluated for
each node and Link and for each scenario
Network resilience indicators are evaluated for
each scenario
---- = Output
---- = comment
Quality
L0 = initial losses
TR = recovery time
Infrastructure
representation
Hazard
Analysis
Protection
analysis
Performance
analysis
Resilience Assessment
Network
Level
1
2 System Recovery functionD
** Picture taken from:
Decò A., Bocchini P., Frangopol D.M.. A probabilistic approach for the prediction of seismic resilience of bridges.
Earthquake Engineering and Structural Dynamics, Wiley, DOI: 10.1002/eqe.2282
Recovery
analysis
**
3
RISE
framework for resilience assessment

18. Francesco Petrini.
francesco.petrini@ustronger2012.com
Real application of the resilience concept
A strategic infrastructure for water supply (serving about 1,300,000 people)

19. 19
Francesco Petrini. Co-founder and
Director
ResilienceWorkshop.RomeJuly02-032014 Real application of the resilience concept
A strategic infrastructure for water supply (serving about 1,300,000 people)

20. 20
Seismic Action
Francesco Petrini. Co-founder and
Director
ResilienceWorkshop.RomeJuly02-032014

21. 21
Critical Node
Francesco Petrini. Co-founder and
Director
ResilienceWorkshop.RomeJuly02-032014

22. Energy and water supply infrastructure: representation
WU
WD
HY
CBCR
CU
RETAINING WALL UP (WU) RETAINING WALL DOWN (WD) HYDROELECTRIC POWER STATION (HY)
CONDUIT UP (CU) CONDUIT ROSALBA
CONDUIT PAVONCELLI BIS
1
2
3
4
5
6
7
1 2 3
4 5 6
7
HYDRAULIC JUNCTION
ELECTRICITY
WATER
Infrastructure plan view Individuation of the system/network components Representation of the system
Outputs
Network Model for
resilience
Multi-hazard
Scenarios
Network
Level
Infrastructure
representation
Hazard
Analysis
1 Load
Network Model for
resilience
Multi-hazard
Scenarios
Local
Level
Network
Level
Local resilience indicators Network resilience indicators
ASSESSMENTandMITIGATION
(Analysisforeachnodeandlink)
Scenario output before mitigation
Scenario output after mitigation
ResISt
framework for resilience assessment
Structure performanceA
B Recovery
E.g. Repair time
Damage
Action
Damage/Disservice
% of rescued
Action values
IM
A
IM
100 %
People safetyB
Quality
Indicator
Status of nodes and links
(no interaction)
A
Quality
Indicator
Interactions effects (quality drop)B
L0
i TR
i
Quality (network level)
Combination of local indicators
Indicator
L0 TR
Resilience ∞ 1 /A
C
Local resilience indicators are evaluated for
each node and Link and for each scenario
Network resilience indicators are evaluated for
each scenario
---- = Output
---- = comment
Quality
L0 = initial losses
TR = recovery time
Infrastructure
representation
Hazard
Analysis
Protection
analysis
Performance
analysis
Resilience Assessment
Network
Level
1
2 System Recovery functionD
** Picture taken from:
Decò A., Bocchini P., Frangopol D.M.. A probabilistic approach for the prediction of seismic resilience of bridges.
Earthquake Engineering and Structural Dynamics, Wiley, DOI: 10.1002/eqe.2282
Recovery
analysis
**
3
RISE
framework for resilience assessment
Francesco Petrini. Co-founder and
Director
ResilienceWorkshop.RomeJuly02-032014

23. 23
System with Elements connected in Parallel
www.francobontempi.org
Str
o N
GER

24. 24
www.francobontempi.org
Str
o N
GER
Damage at Local Level

25. 25
www.francobontempi.org
Str
o N
GER
Damage at Element Level

26. 26
www.francobontempi.org
Str
o N
GER
Damage at Structure Level

27. Energy and water supply infrastructure: scenarios
FLOW REDUCTION (U)FLOW REDUCTION (R)
ELECTRIC POWER INTERRUPTIONTOTAL FLOW INTERRUPTION (R+U)
Consequencescenarios Network Model for
resilience
Multi-hazard
Scenarios
Network
Level
Infrastructure
representation
Hazard
Analysis
1 Load
Network Model for
resilience
Multi-hazard
Scenarios
Local
Level
Network
Level
Local resilience indicators Network resilience indicators
ASSESSMENTandMITIGATION
(Analysisforeachnodeandlink)
Scenario output before mitigation
Scenario output after mitigation
ResISt
framework for resilience assessment
Structure performanceA
B Recovery
E.g. Repair time
Damage
Action
Damage/Disservice
% of rescued
Action values
IM
A
IM
100 %
People safetyB
Quality
Indicator
Status of nodes and links
(no interaction)
A
Quality
Indicator
Interactions effects (quality drop)B
L0
i TR
i
Quality (network level)
Combination of local indicators
Indicator
L0 TR
Resilience ∞ 1 /A
C
Local resilience indicators are evaluated for
each node and Link and for each scenario
Network resilience indicators are evaluated for
each scenario
---- = Output
---- = comment
Quality
L0 = initial losses
TR = recovery time
Infrastructure
representation
Hazard
Analysis
Protection
analysis
Performance
analysis
Resilience Assessment
Network
Level
1
2 System Recovery functionD
** Picture taken from:
Decò A., Bocchini P., Frangopol D.M.. A probabilistic approach for the prediction of seismic resilience of bridges.
Earthquake Engineering and Structural Dynamics, Wiley, DOI: 10.1002/eqe.2282
Recovery
analysis
**
3
RISE
framework for resilience assessment
Francesco Petrini. Co-founder and
Director
ResilienceWorkshop.RomeJuly02-032014

28. WU FAIL
HY
FAIL?
CU
FAIL?
Y
WU + WD +HY+ CU
TOTAL FLOW
TOTAL FLOW
TOTAL FLOW
NO R + E
CR
FAIL?
WU
WU + WD
WU + WD + HY
WD
FAIL?
N
N
N
Y
Y
N
N
N
N
CR
FAIL?
CR
FAIL?
CR
FAIL?
NO R
NO R
NO U + E
NO U+ E + R
N
N
N
N
Y
Y
Y
Y
Fault-Treeanalysis
Criticalseriesofcomponents
WU
WD
HY
CBCR
CU
Energy and water supply infrastructure: scenarios
Network Model for
resilience
Multi-hazard
Scenarios
Network
Level
Infrastructure
representation
Hazard
Analysis
1 Load
Network Model for
resilience
Multi-hazard
Scenarios
Local
Level
Network
Level
Local resilience indicators Network resilience indicators
ASSESSMENTandMITIGATION
(Analysisforeachnodeandlink)
Scenario output before mitigation
Scenario output after mitigation
ResISt
framework for resilience assessment
Structure performanceA
B Recovery
E.g. Repair time
Damage
Action
Damage/Disservice
% of rescued
Action values
IM
A
IM
100 %
People safetyB
Quality
Indicator
Status of nodes and links
(no interaction)
A
Quality
Indicator
Interactions effects (quality drop)B
L0
i TR
i
Quality (network level)
Combination of local indicators
Indicator
L0 TR
Resilience ∞ 1 /A
C
Local resilience indicators are evaluated for
each node and Link and for each scenario
Network resilience indicators are evaluated for
each scenario
---- = Output
---- = comment
Quality
L0 = initial losses
TR = recovery time
Infrastructure
representation
Hazard
Analysis
Protection
analysis
Performance
analysis
Resilience Assessment
Network
Level
1
2 System Recovery functionD
** Picture taken from:
Decò A., Bocchini P., Frangopol D.M.. A probabilistic approach for the prediction of seismic resilience of bridges.
Earthquake Engineering and Structural Dynamics, Wiley, DOI: 10.1002/eqe.2282
Recovery
analysis
**
3
RISE
framework for resilience assessment
Francesco Petrini. Co-founder and
Director
ResilienceWorkshop.RomeJuly02-032014

29. Load
Network Model for
resilience
Multi-hazard
Scenarios
Local
Level
Network
Level
Local resilience indicators Network resilience indicators
ASSESSMENTandMITIGATION
(Analysisforeachnodeandlink)
Scenario output before mitigation
Scenario output after mitigation
ResISt
framework for resilience assessment
Structure performanceA
B Recovery
E.g. Repair time
Damage
Action
Damage/Disservice
% of rescued
Action values
IM
A
IM
100 %
People safetyB
Quality
Indicator
Status of nodes and links
(no interaction)
A
Quality
Indicator
Interactions effects (quality drop)B
L0
i TR
i
Quality (network level)
Combination of local indicators
Indicator
L0 TR
Resilience ∞ 1 /A
C
Local resilience indicators are evaluated for
each node and Link and for each scenario
Network resilience indicators are evaluated for
each scenario
---- = Output
---- = comment
Quality
L0 = initial losses
TR = recovery time
Infrastructure
representation
Hazard
Analysis
Protection
analysis
Performance
analysis
Resilience Assessment
Network
Level
1
2 System Recovery functionD
** Picture taken from:
Decò A., Bocchini P., Frangopol D.M.. A probabilistic approach for the prediction of seismic resilience of bridges.
Earthquake Engineering and Structural Dynamics, Wiley, DOI: 10.1002/eqe.2282
Recovery
analysis
**
3
RISE
framework for resilience assessment
Load
Local
Level
ASSESSMENTandMITIGATION
(Analysisforeachnodeandlink)
Structure performanceA
B Recovery
E.g. Repair time
Damage
Action
Damage/Disservice
% of rescued
Action values
IM
A
IM
100 %
People safetyB
Protection
analysis
Performance
analysis
2
Critical series of components: retaining walls
WU
WD
HY
CBCR
CU
(0,0) (92,0)
(92,29)
(0,29)
(0,54)
(0,62) (28.5,62)
(53,56)
(63,45)
(92,32)
(92,34)
Critical series of components
FE model

30. Interactions on seismic fragility
Load
Network Model for
resilience
Multi-hazard
Scenarios
Local
Level
Network
Level
Local resilience indicators Network resilience indicators
ASSESSMENTandMITIGATION
(Analysisforeachnodeandlink)
Scenario output before mitigation
Scenario output after mitigation
ResISt
framework for resilience assessment
Structure performanceA
B Recovery
E.g. Repair time
Damage
Action
Damage/Disservice
% of rescued
Action values
IM
A
IM
100 %
People safetyB
Quality
Indicator
Status of nodes and links
(no interaction)
A
Quality
Indicator
Interactions effects (quality drop)B
L0
i TR
i
Quality (network level)
Combination of local indicators
Indicator
L0 TR
Resilience ∞ 1 /A
C
Local resilience indicators are evaluated for
each node and Link and for each scenario
Network resilience indicators are evaluated for
each scenario
---- = Output
---- = comment
Quality
L0 = initial losses
TR = recovery time
Infrastructure
representation
Hazard
Analysis
Protection
analysis
Performance
analysis
Resilience Assessment
Network
Level
1
2 System Recovery functionD
** Picture taken from:
Decò A., Bocchini P., Frangopol D.M.. A probabilistic approach for the prediction of seismic resilience of bridges.
Earthquake Engineering and Structural Dynamics, Wiley, DOI: 10.1002/eqe.2282
Recovery
analysis
**
3
RISE
framework for resilience assessment
Local resilience indicators
Quality
Indicator
Status of nodes and links
(no interaction)
A
Quality
Indicator
Interactions effects (quality drop)B
L0
i TR
i
Local resilience indicators are evaluated for
each node and Link and for each scenario
IM (g)
P(EDP|IM)
WUWU WDWD++
Francesco Petrini. Co-founder and
Director
ResilienceWorkshop.RomeJuly02-032014
(0,0) (92,0)
(92,29)
(0,29)
(0,54)
(0,62) (28.5,6
2)
(53,56)
(63,45)
(92,32)
(92,34)
WUWU
WDWD

31. Francesco Petrini.
francesco.petrini@ustronger2012.com
ONGOING: Real application of the resilience concept
Structural analysis of sea port defence structures for durability and robustness

32. ONGOING: Real application of the resilience concept
Structural analysis of sea port defence structures for durability and robustness
www.francobontempi.org
Str
o N
GER

33. ONGOING: Real application of the resilience concept
Structural analysis of sea port defence structures for durability and robustness
www.francobontempi.org
Str
o N
GER

34. “…. to provide, through innovation,
advanced products and services for a
sustainable and safe world.”
StroNGER – Vision
ResilienceWorkshop.RomeJuly02-032014
www.stronger2012.com